Parallel data collection and recovery for failing virtual computer processing system

ABSTRACT

Techniques for parallel data collection and recovery for a failing virtual processing system are disclosed. According to aspects of the present disclosure, an example method includes: detecting that the virtual processing system experiences an irreparable error; saving, by each of a plurality of processors of the physical processing system, a corresponding context and data stored in an allocated portion of a memory of the physical processing system to a data store; selecting one of the plurality of processors as a recovery processor; initializing, by the recovery processor, a pre-determined reserved portion of the memory; initiating, by the recovery processor, a new instance of the virtual processing system on the reserved portion of the memory while each remaining processor of the plurality of processors continues the saving; and dynamically adding each remaining processor of the plurality of processors to the new instance of the virtual processing system.

DOMESTIC PRIORITY

The present application is a continuation of U.S. patent applicationSer. No. 15/174,129, entitled “PARALLEL DATA COLLECTION AND RECOVERY FORFAILING VIRTUAL COMPUTER PROCESSING SYSTEM,” filed Jun. 6, 2016, thedisclosure of which is incorporated by reference herein in its entirety.

BACKGROUND

The present disclosure relates to computer processing systems, and moreparticularly to the parallel data collection and recovery of a failingvirtual processing system.

Physical processing systems (or computing hosts) may utilize virtualprocessing systems (or computing guests) to virtualize operating systemsand/or applications. Such systems typically leverage hypervisortechnology to create and manage the many aspects of virtualizedcomputing. For the purposes of this disclosure, a “virtual processingsystem” can refer to the entire system providing such a virtualizedenvironment or to a single virtualized computing guest therebysupported. Any component of these systems may reach an erroneous andunrecoverable state during runtime, often necessitating a system-widefailure. At failure-time, it is important to collect the current stateof the processors and memory of the physical processing system to allowfor the underlying problem's subsequent analysis. It is also importantto commence a recovery procedure, which may include re-initializing thephysical processing system's hardware components before restarting thevirtual processing system.

SUMMARY

According to examples of the present disclosure, techniques includingmethods, systems, and/or computer program products for parallel datacollection and recovery for a failing virtual processing system areprovided. An example method may include: detecting that the virtualprocessing system experiences an irreparable error; saving, by each of aplurality of processors of the physical processing system, acorresponding context and data stored in an allocated portion of amemory of the physical processing system to a data store; selecting oneof the plurality of processors as a recovery processor; initializing, bythe recovery processor, a pre-determined reserved portion of the memory;initiating, by the recovery processor, a new instance of the virtualprocessing system on the reserved portion of the memory while eachremaining processor of the plurality of processors continues the saving;and dynamically adding each remaining processor of the plurality ofprocessors to the new instance of the virtual processing system.

Additional features and advantages are realized through the techniquesof the present disclosure. Other aspects are described in detail hereinand are considered a part of the disclosure. For a better understandingof the present disclosure with the advantages and the features, refer tothe following description and to the drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The subject matter which is regarded as the invention is particularlypointed out and distinctly claimed in the claims at the conclusion ofthe specification. The foregoing and other features, and advantagesthereof, are apparent from the following detailed description taken inconjunction with the accompanying drawings in which:

FIGS. 1A, 1B and 1C illustrate a block diagram of a physical processingsystem that provides the computing resources for a virtual processingsystem, and that executes parallel data collection and recoveryaccording to examples of the present disclosure;

FIG. 2 illustrates a flow diagram of a computer-implemented method forparallel data collection and recovery for a failing virtual processingsystem according to examples of the present disclosure;

FIG. 3 illustrates a block diagram of a processing system forimplementing the techniques described herein according to examples ofthe present disclosure;

FIG. 4 illustrates a cloud computing environment according to examplesof the present disclosure; and

FIG. 5 illustrates abstraction model layers according to examples of thepresent disclosure.

DETAILED DESCRIPTION

Current approaches for failure-time data collection and recovery utilizeseparate processes that are time-consuming and dependent on sequentialexecution. Data recovery may take approximately thirty to sixty minutesto complete, although other time periods for data recovery are possible.Re-initializing the virtual processing system may take anotherapproximately sixty minutes thereafter, although this time may beshorter or longer depending on system performance and other variables.During both phases, the virtual processing system is unavailable tousers, which may have a significant impact and/or cost to stakeholdersin the system's reliability. Current approaches do not perform these twophases in parallel principally because the state of memory must bepreserved for (and throughout) data collection.

The present techniques solve these problems by parallelizing datacollection and recovery for a failing virtual processing systemaccording to the various implementations described herein. Thesetechniques apply to physical processing systems running virtualprocessing systems and to physical processing systems running a nativeoperating system without any virtual processing systems.

In some implementations, the present techniques significantly reducedowntime by parallelizing the data collection and recovery aspectsassociated with recovering from a system failure. Moreover, byinitializing a new instance of the virtual processing system while thesystem is logging its state to persistent storage, a user may experienceat least partial system restoration much earlier than with previoustechniques. These and other advantages will be apparent from thedescription that follows.

FIGS. 1A-1C illustrate a block diagram of a physical processing system100 for demonstrating the applications of parallel data collection andrecovery for a failing virtual processing system (e.g., a system with atleast one virtual machine, for example, virtual machine 102 a) accordingto examples of the present disclosure. Physical processing system 100includes a plurality of processors 110 a, 110 b, 110 c, 110 d, 110 e,110 f, 110 g, 110 h, 110 i, 110 j, 110 k, 110 l (referred tocollectively as “processors 110”), a memory 120, and a data store 130.It should be appreciated that the data store 130 may be a persistentmemory, such as non-volatile memory, flash memory, or other suitablememory for storing data. In aspects of the present disclosure, thephysical processing system 100 also includes a hypervisor program (notshown), which plays a silent role in the organization of the presentsystem hierarchy by design.

The physical processing system 100 provides computing resources for avirtual machine 102 a, which utilizes the processors 110 and the memory120. In aspects of the present disclosure, the virtual machine 102 autilizes an allocated portion 122 of the memory 120. The allocatedportion 122 represents a portion of the memory 120 available to thevirtual machine 102 a. A reserved portion 124 of the memory isunavailable to the virtual machine 102 a and is reserved for therecovery of the virtual processing system when an unrecoverable or fatalerror occurs.

Upon the occurrence of a crash-inducing failure, each of the processors110 begins storing their respective statuses into the data store 130. Asillustrated in FIG. 1B, one of the processors 110 (i.e., the firstprocessor that stores its status in the data store 130 is selected andre-purposed to initiate a new instance of the virtual processing system.The new instance of the virtual machine 102 b is initiated as part ofthe new virtual processing system, while the remaining processors 110(i.e., processors 110 b-110 l of FIG. 1B) continue to save theirrespective statuses to the data store 130.

Upon initiation, the new virtual processing system has one assignedprocessor (e.g., processor 110 a) to support virtual machine 102 b. Thevirtual machine 102 b uses as its central storage the reserved portion124 of the memory 120 originally provided during installation of thephysical processing system 100.

The processor 110 a handles the initialization of the virtual machine102 b until additional processors 110 finish saving their status. Aseach processor completes saving its status, it can be dynamically addedto the virtual processing system and therefore serve as a resource tovirtual machine 102 b, as illustrated in FIG. 1C.

Finally, once the data collection process is complete, the virtualmachine 102 b begins utilizing a portion of the memory 120 previouslyallocated to the virtual machine 102 a, and data can be reloaded to thevirtual machine 102 b from the data store 130. Similarly, the processors110 can be returned to their original state (i.e., the state saved asthe status upon the error occurring) or reset completely to reach aclean starting point.

Although the virtual machine 102 b begins utilizing a portion of thememory 120 that was previously reserved, a new portion of the memory 120is re-reserved (i.e., re-reserved portion 128) to be available forfuture data collection and recovery of a new virtual processing system.

According to examples of the present disclosure, the virtual machines102 a, 102 b are managed by a hypervisor instance that could besupporting additional virtual machines. One or more of these virtualmachines may have to be migrated to the previously reserved memorydepending on the severity of the failure. If the hypervisor itselfcrashes, an entirely new virtual memory processing system may be builtstarting with the reserved memory and recovery processor as physicalresources.

FIG. 2 illustrates a flow diagram of a method 200 for parallel datacollection and recovery for a failing virtual processing systemaccording to examples of the present disclosure. The method 200 may beperformed, for example, by the physical processing system 100 of FIGS.1A-1C and/or by the processing system 20 of FIG. 3. The method 200begins at block 202 and continues to block 204.

At block 204, the method 200 includes detecting, by the physicalprocessing system (e.g., physical processing system 100) or by ahypervisor, that the virtual processing system experiences anirreparable error.

At block 206, the method 200 includes saving, by each of a plurality ofprocessors (e.g., processors 110) of the physical processing system, acorresponding context and data stored in an allocated portion (e.g.,allocated portion 122) of a memory (e.g., memory 120) of the physicalprocessing system to a data store.

At block 208, the method 200 includes selecting one of the plurality ofprocessors (e.g., processor 110 a) as a recovery processor. In someexamples, such as especially time-critical cases, the recovery processorcan be selected as being the first processor to complete the saving. Inother cases, a particular processor can be predetermined to be therecovery processor. As another option, the recovery processor can be anadditional processor not associated with the failing virtual processingsystem (i.e., the recovery processor is an extra processor). In thiscase, the recovery processor is enabled upon the detection of theirreparable error.

At block 210, the method 200 includes initializing, by the recoveryprocessor, a pre-determined reserved portion of the memory (e.g.,reserved portion 124). An alternative to reserving memory for recoveryis to utilize memory as the data is saved and the memory becomesunallocated just as with the processing system. The initializing mayinclude powering on or otherwise enabling the reserved portion of thememory.

At block 212, the method 200 includes initiating, by the recoveryprocessor, a new instance of the virtual processing system on thereserved portion of the memory while each remaining processor of theplurality of processors continues the saving their own status and thestate of memory (e.g., allocated portion 122).

At block 214, the method 200 includes dynamically adding each remainingprocessor of the plurality of processors to the new instance of thevirtual processing system. In examples, each remaining processor (e.g.,processors 110 b-110 l) is migrated to the new instance of the virtualprocessing system upon completion of the saving of the context for thatprocessor.

The method 200 continues to block 216 and ends.

Additional processes also may be included. For example, the allocatedportion of the memory becomes an unallocated portion of the memory uponcompletion of the saving. In such cases, the method 200 includesdesignating a first portion of the unallocated portion of the memory tothe new instance of the virtual processing system and reserving a secondportion of the unallocated portion of the memory as a new reservedportion of the memory. In some examples, the virtual processing systemis a first instance of a hypervisor, and the new instance of the virtualprocessing system is a second instance of a hypervisor.

It should be understood that the processes depicted in FIG. 2 representillustrations, and that other processes may be added or existingprocesses may be removed, modified, or rearranged without departing fromthe scope and spirit of the present disclosure.

It is understood in advance that the present disclosure is capable ofbeing implemented in conjunction with any other type of computingenvironment now known or later developed. For example, FIG. 3illustrates a block diagram of a processing system 20 for implementingthe techniques described herein. In examples, processing system 20 hasone or more central processing units (processors) 21 a, 21 b, 21 c, etc.(collectively or generically referred to as processor(s) 21 and/or asprocessing device(s)). In aspects of the present disclosure, eachprocessor 21 may include a reduced instruction set computer (RISC)microprocessor. Processors 21 are coupled to system memory (e.g., randomaccess memory (RAM) 24) and various other components via a system bus33. Read only memory (ROM) 22 is coupled to system bus 33 and mayinclude a basic input/output system (BIOS), which controls certain basicfunctions of processing system 20.

Further illustrated are an input/output (I/O) adapter 27 and acommunications adapter 26 coupled to system bus 33. I/O adapter 27 maybe a small computer system interface (SCSI) adapter that communicateswith a hard disk 23 and/or a tape storage drive 25 or any other similarcomponent. I/O adapter 27, hard disk 23, and tape storage device 25 arecollectively referred to herein as mass storage 34. Operating system 40for execution on processing system 20 may be stored in mass storage 34.A network adapter 26 interconnects system bus 33 with an outside network36 enabling processing system 20 to communicate with other such systems.

A display (e.g., a display monitor) 35 is connected to system bus 33 bydisplay adaptor 32, which may include a graphics adapter to improve theperformance of graphics intensive applications and a video controller.In one aspect of the present disclosure, adapters 26, 27, and/or 32 maybe connected to one or more I/O busses that are connected to system bus33 via an intermediate bus bridge (not shown). Suitable I/O buses forconnecting peripheral devices such as hard disk controllers, networkadapters, and graphics adapters typically include common protocols, suchas the Peripheral Component Interconnect (PCI). Additional input/outputdevices are shown as connected to system bus 33 via user interfaceadapter 28 and display adapter 32. A keyboard 29, mouse 30, and speaker31 may be interconnected to system bus 33 via user interface adapter 28,which may include, for example, a Super I/O chip integrating multipledevice adapters into a single integrated circuit.

In some aspects of the present disclosure, processing system 20 includesa graphics processing unit 37. Graphics processing unit 37 is aspecialized electronic circuit designed to manipulate and alter memoryto accelerate the creation of images in a frame buffer intended foroutput to a display. In general, graphics processing unit 37 is veryefficient at manipulating computer graphics and image processing, andhas a highly parallel structure that makes it more effective thangeneral-purpose CPUs for algorithms where processing of large blocks ofdata is done in parallel.

Thus, as configured herein, processing system 20 includes processingcapability in the form of processors 21, storage capability includingsystem memory (e.g., RAM 24), and mass storage 34, input means such askeyboard 29 and mouse 30, and output capability including speaker 31 anddisplay 35. In some aspects of the present disclosure, a portion ofsystem memory (e.g., RAM 24) and mass storage 34 collectively store anoperating system such as the AIX® operating system from IBM Corporationto coordinate the functions of the various components shown inprocessing system 20.

In other examples, the present disclosure may be implemented on cloudcomputing. Cloud computing is a model of service delivery for enablingconvenient, on-demand network access to a shared pool of configurablecomputing resources (e.g. networks, network bandwidth, servers,processing, memory, storage, applications, virtual machines, andservices) that can be rapidly provisioned and released with minimalmanagement effort or interaction with a provider of the service. Thiscloud model may include at least five characteristics, at least threeservice models, and at least four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 4, illustrative cloud computing environment 50 isillustrated. As shown, cloud computing environment 50 comprises one ormore cloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 4 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 5, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 4) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 5 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As illustrated, the following layersand corresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provides pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and parallel data collection and recovery fora failing virtual processing system 96.

The present techniques may be implemented as a system, a method, and/ora computer program product. The computer program product may include acomputer readable storage medium (or media) having computer readableprogram instructions thereon for causing a processor to carry outaspects of the present disclosure.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present disclosure may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some examples, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present disclosure.

Aspects of the present disclosure are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to aspects of thepresent disclosure. It will be understood that each block of theflowchart illustrations and/or block diagrams, and combinations ofblocks in the flowchart illustrations and/or block diagrams, can beimplemented by computer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousaspects of the present disclosure. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The descriptions of the various examples of the present disclosure havebeen presented for purposes of illustration, but are not intended to beexhaustive or limited to the embodiments disclosed. Many modificationsand variations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the described techniques.The terminology used herein was chosen to best explain the principles ofthe present techniques, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the techniquesdisclosed herein.

What is claimed is:
 1. A computer-implemented method for parallel datacollection and system recovery for a failing virtual processing systemexecuting on a physical processing system, the method comprising:saving, by each of a plurality of processors of the physical processingsystem, a corresponding context and data stored in an allocated portionof a memory of the physical processing system to a data store; selectingone of the plurality of processors as a recovery processor;initializing, by the recovery processor, a pre-determined reservedportion of the memory; and initiating, by the recovery processor, a newinstance of the virtual processing system on the reserved portion of thememory while each remaining processor of the plurality of processorscontinues the saving.
 2. The computer-implemented method of claim 1,further comprising, prior to the saving, detecting that the virtualprocessing system experiences an irreparable error, wherein the recoveryprocessor is selected as being first to complete the saving.
 3. Thecomputer-implemented method of claim 2, wherein the detecting isperformed by one of the physical processing system and a hypervisor. 4.The computer-implemented method of claim 1, wherein each remainingprocessor is dynamically added to the new instance of the virtualprocessing system upon completion of the saving of the context for thatprocessor.
 5. The computer-implemented method of claim 1, wherein theallocated portion of the memory becomes an unallocated portion of thememory upon completion of the saving.
 6. The computer-implemented methodof claim 5, further comprising: designating a first portion of theunallocated portion of the memory to the new instance of the virtualprocessing system; and reserving a second portion of the unallocatedportion of the memory as a new reserved portion of the memory.
 7. Thecomputer-implemented method of claim 1, wherein the data store is apersistent memory.
 8. The computer-implemented method of claim 1,wherein the virtual processing system is a first instance of ahypervisor, and wherein the new instance of the virtual processingsystem is a second instance of a hypervisor.
 9. The computer-implementedmethod of claim 1, further comprising: dynamically adding each remainingprocessor of the plurality of processors to the new instance of thevirtual processing system.
 10. A system for parallel data collection andsystem recovery for a failing virtual processing system executing on aphysical processing system, the system comprising: a memory havingcomputer readable instructions; and a processing device for executingthe computer readable instructions, the computer readable instructionscomprising: saving, by each of a plurality of processors of the physicalprocessing system, a corresponding context and data stored in anallocated portion of a memory of the physical processing system to adata store; selecting one of the plurality of processors as a recoveryprocessor; initializing, by the recovery processor, a pre-determinedreserved portion of the memory; and initiating, by the recoveryprocessor, a new instance of the virtual processing system on thereserved portion of the memory while each remaining processor of theplurality of processors continues the saving.
 11. The system of claim10, the computer readable instructions further comprising, prior to thesaving, detecting that the virtual processing system experiences anirreparable error, wherein the recovery processor is selected as beingfirst to complete the saving.
 12. The system of claim 11, wherein thedetecting is performed by one of the physical processing system and ahypervisor.
 13. The system of claim 10, wherein each remaining processoris dynamically added to the new instance of the virtual processingsystem upon completion of the saving of the context for that processor.14. The system of claim 10, wherein the allocated portion of the memorybecomes an unallocated portion of the memory upon completion of thesaving.
 15. The system of claim 14, the computer readable instructionsfurther comprising: designating a first portion of the unallocatedportion of the memory to the new instance of the virtual processingsystem; and reserving a second portion of the unallocated portion of thememory as a new reserved portion of the memory.
 16. The system of claim10, wherein the data store is a persistent memory.
 17. The system ofclaim 10, wherein the virtual processing system is a first instance of ahypervisor, and wherein the new instance of the virtual processingsystem is a second instance of a hypervisor.
 18. The system of claim 10,the computer readable instructions further comprising: dynamicallyadding each remaining processor of the plurality of processors to thenew instance of the virtual processing system.
 19. A computer programproduct for parallel data collection and system recovery for a failingvirtual processing system executing on a physical processing system, thecomputer program product comprising: a non-transitory computer readablestorage medium having program instructions embodied therewith, theprogram instructions executable by a processing device to cause theprocessing device to: save, by each of a plurality of processors of thephysical processing system, a corresponding context and data stored inan allocated portion of a memory of the physical processing system to adata store; select one of the plurality of processors as a recoveryprocessor; initialize, by the recovery processor, a pre-determinedreserved portion of the memory; and initiate, by the recovery processor,a new instance of the virtual processing system on the reserved portionof the memory while each remaining processor of the plurality ofprocessors continues the saving.
 20. The computer program product ofclaim 19, wherein the processor device is further configured to:dynamically adding each remaining processor of the plurality ofprocessors to the new instance of the virtual processing system.